Continuous-time dynamical systems mean that the system's behavior changes with time development in the continuous-time domain. There have been related works that view data as a continuous object in artificial intelligence, e.g., pictures [1]} and static graphs [2]}, [3]}. The continuous-time dynamic graph (CTDG) we introduced in Section REF  is also a continuous-time dynamical system in which nodes' state changes over time. Therefore, it is necessary to model the continuous dynamical system of CTDG data. To the best of our knowledge, our CTGN is the first approach that learn continuous-time dynamics on CTDG.
